In the field of Digital Pathology, there is a requirement to have an exchange of studies for the purpose of a primary or secondary pathological diagnosis. Studies typically consist of one or more lower-resolution images, the references to the corresponding higher-resolution images, associated image metadata, study metadata and patient metadata. Further, access is provided to the necessary data to perform the proper review of the study. Physical and security-based constraints to this access represent a primary barrier to wide scale deployment of Digital Pathology systems. The physical constraints include bandwidth and storage issues for local and remote access, and are typical of most networked applications with the additional requirements imposed by the exceedingly high resolution nature of the data. Additionally, given the sensitivity of medical data, security based constraints, such as ensuring patient privacy and data security are the key areas needing additional focus in this field.
Digital Pathology, in itself, is a compelling enough technology to reach widespread adoption in all but the smallest of practices. The reduction in cost, time and management headache of no longer needing to distribute glass slides to in-house physicians, to second opinion or referrals, to search for slides for publications and presentations will quickly prove itself invaluable, as the workflow of slide production, digitization and immediate archival comes to be. Further, being able to transform, reduce or restrict the data being sent to a user can increase the diagnostic ability of a user, can increase the number of users who can benefit from the data and provide more efficient access to the data.
Digital Pathology provides the opportunity to apply additional processing and analysis on behalf of the user as part of the process, allowing new modalities of diagnosis for the field of Pathology.
Digital Pathology can, as Health Informatics has, enable the filtering of sensitive patient data from a study, allowing the studies use beyond the scope of the hospital, as an educational or research dataset. Structured and encoded information allows new forms of access and distribution of data through the compression, progressive and predictive packaging of the data. Examples of the predictive packaging include only sending the data which the user requires, a resource and bandwidth optimized manner.